• 제목/요약/키워드: algorithms

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에너지소산 제어 알고리듬의 제어이득 산정 (Control-Gain Estimation of Energy Dissipation Control Algorithms)

  • 이상현;민경원;강상훈
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2004년도 봄 학술발표회 논문집
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    • pp.431-438
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    • 2004
  • This study is on control-gain estimation of energy dissipation control algorithms. Velocity feedback, bang-bang, and energy dissipation control algorithms are proposed based on the Lyapunov stability theory and their performances are evaluated and compared. Saturation problem is considered in the design of the velocity feedback and energy dissipation control algorithms, and chattering problem in bang-bang control is solved by using boundary layer. Numerical results show that the proposed control algorithms can dissipate the structural energy induced by wind loads efficiently, and thus provide good control performance.

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Evaluation system of dynamically changing cryptographic algorithms using the SEBSW-1:PCI-based encryption and decryption PC board

  • Kajisaki, Hirotsugu;Kurokawa, Takakazu
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -1
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    • pp.145-148
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    • 2002
  • In a network communication process, cryptographic algorithms play important role for secure process. This paper presents a new system architecture named "DCCS." This system can handle flexible operations of both cryptographic algorithms and the keys. For experimental evaluation, two representative cryptographic algorithms DES and Triple-DES are designed and implemented into an FPGA chip on the SEBSW-1. Then the developed board is confirmed to change its cryptographic algorithms dynamically. Also its throughput confirmed the ability of the real-time net-work use of the designed system.

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유전 알고리즘과퍼지 푸론 시스템의 합성 (Fusion of Genetic Algorithms and Fuzzy Inference System)

  • 황희수;오성권;우광방
    • 대한전기학회논문지
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    • 제41권9호
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    • pp.1095-1103
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    • 1992
  • An approach to fuse the fuzzy inference system which is able to deal with imprecise and uncertain information and genetic algorithms which display the excellent robustness in complex optimization problems is presented in this paper. In order to combine genetic algorithms and fuzzy inference engine effectively the new reasoning method is suggested. The efficient identification method of fuzzy rules is proposed through the adjustment of search areas of genetic algorithms. The feasibilty of the proposed approach is evaluated through simulation.

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조기완료 및 납기지연 벌과금을 고려한 흐름작업 시스템의 일정계획 (A Study on Flow Shop Scheduling with Early & Tardy Penalty Cost)

  • 이정환
    • 산업경영시스템학회지
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    • 제16권27호
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    • pp.91-104
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    • 1993
  • This paper is concerned with flow shop scheduling problems having the common due date. V-shape property is used for algorithms with early and tardy penalty cost. The objective of this paper is developing efficient heuristic scheduling algorithms for minimizing total penalty cost function and determining the optimal common due date. The between job delay and the work in process are considered for developing algorithms as penalty cost. Algorithms is simulated to analyze interrelated factors. A numerical example is given for illustrating the proposed algorithms.

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Optimal Configuration of Distribution Network using Genetic Algorithms

  • Kim, Intaek;Wonhyuk Cho
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.625-628
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    • 1998
  • This paper presents an application of genetic algorithms(GAs) for optimal configuration of distribution network. Three problems have been used to show how genetic algorithms are modified and applied. Solutions to the problems are found by minimizing the cost function which is directly related with balancing the loads. Simulation results show that genetic algorithms are technically feasible if they are tailored to meet the needs of real problems.

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Flow based heuristics for the multiple traveling salesman problem with time windows

  • Lee, Myung-Sub
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 1993년도 춘계공동학술대회 발표논문 및 초록집; 계명대학교, 대구; 30 Apr.-1 May 1993
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    • pp.354-366
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    • 1993
  • In this paper, new algorithms for solving the multiple traveling salesman problem with time windows are presented. These algorithms are based on the flow based algorithms for solving the vehicle scheduling problem. Computational results on problems up to 750 customers indicate that these algorithms produce superior results to existing heuristic algorithms for solving the vehicle routing problems when the time windows are 'tight enough' where 'tight enough' is based on a metric proposed by desrosiers et al.(1987).

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SCALING METHODS FOR QUASI-NEWTON METHODS

  • MOGHRABI, ISSAM A.R.
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제6권1호
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    • pp.91-107
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    • 2002
  • This paper presents two new self-scaling variable-metric algorithms. The first is based on a known two-parameter family of rank-two updating formulae, the second employs an initial scaling of the estimated inverse Hessian which modifies the first self-scaling algorithm. The algorithms are compared with similar published algorithms, notably those due to Oren, Shanno and Phua, Biggs and with BFGS (the best known quasi-Newton method). The best of these new and published algorithms are also modified to employ inexact line searches with marginal effect. The new algorithms are superior, especially as the problem dimension increases.

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Generalized Robust Multichannel Frequency-Domain LMS Algorithms for Blind Channel Identification

  • Chung, Ik-Joo;Clements, Mark A.
    • ETRI Journal
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    • 제34권1호
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    • pp.130-133
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    • 2012
  • Recently, several noise-robust adaptive multichannel LMS algorithms have been proposed based on the spectral flatness of the estimated channel coefficients in the presence of additive noise. In this work, we propose a general form for the algorithms that integrates the existing algorithms into a common framework. Computer simulation results are presented and demonstrate that a new proposed algorithm gives better performance compared to existing algorithms in noisy environments.

유전자 알고리즘을 이용한 Ball-Beam 시스템의 제어에 관한 연구 (A study of ball-beam system control using genetic algorithms)

  • 이남기;박종범;조황
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.968-971
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    • 1996
  • In this paper, feedback controller is designed for ball-beam system using genetic algorithms. A genetic algorithms are implemented for optimizing gain parameters of feedback controller. We can find optimal point in multi-dimensional search space by using genetic algorithms. Performance of controller is tested by simulation of ball-beam system.

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Review of Data-Driven Multivariate and Multiscale Methods

  • Park, Cheolsoo
    • IEIE Transactions on Smart Processing and Computing
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    • 제4권2호
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    • pp.89-96
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    • 2015
  • In this paper, time-frequency analysis algorithms, empirical mode decomposition and local mean decomposition, are reviewed and their applications to nonlinear and nonstationary real-world data are discussed. In addition, their generic extensions to complex domain are addressed for the analysis of multichannel data. Simulations of these algorithms on synthetic data illustrate the fundamental structure of the algorithms and how they are designed for the analysis of nonlinear and nonstationary data. Applications of the complex version of the algorithms to the synthetic data also demonstrate the benefit of the algorithms for the accurate frequency decomposition of multichannel data.